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Wulfram Gerstner

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Wulfram Gerstner
NationalityGerman
AwardsValentino Braitenberg Award for Computational Neuroscience 2018
Academic background
Alma materUniversity of Tübingen
Ludwig Maximilian University of Munich
Academic work
DisciplineNeuroscience
Sub-disciplineComputational neuroscience
InstitutionsÉcole Polytechnique Fédérale de Lausanne (EPFL)
Main interestsDynamic models neural activity

Spike-timing-dependent plasticity (STDP)
Neuronal coding
Hippocampal models

Spatial representation
Websitehttps://www.epfl.ch/labs/lcn/

Wulfram Gerstner is a German and Swiss computational neuroscientist. His research focuses on neural spiking patterns in neural networks, and their connection to learning, spatial representation and navigation. Since 2006 Gerstner has been a full professor of Computer Science and Life Sciences at École Polytechnique Fédérale de Lausanne (EPFL), where he also serves as a Director of the Laboratory of Computational Neuroscience.[1]

Career

Gerstner studied physics at the University of Tübingen and at the Ludwig Maximilian University of Munich. In 1989, he received his Master's degree with a thesis in experimental quantum optics. He then joined the theoretical biophysics group of William Bialek at University of California, Berkeley as a visiting researcher.[2] He received his PhD in theoretical physics from the Technical University of Munich in 1993 under supervision from Leo van Hemmen. He did postdoctoral work at Brandeis University [3] and at Technical University of Munich,[4] where he worked in theoretical neuroscience.

In 1996 he was nominated as assistant professor and in February 2001 he was promoted as an associate professor with tenure at EPFL. In August 2006 Gerstner was appointed full professor at EPFL in both the School of Computer and Communication Sciences and the School of Life Sciences.[1][5]

Books

  • Spiking Neuron Models: Single neurons, populations, plasticity [6] (Gerstner, W. and Kistler, W.M., 2002, Cambridge University Press) has been influential in defining the field of Spiking Neural Networks.
  • Neuronal dynamics: From single neurons to networks and models of cognition[7] (Gerstner, W., Kistler, W.M., Naud, R. and Paninski, L., 2014, Cambridge University Press) is a textbook in the field of computational neuroscience. The online version of Neuronal Dynamics also contains computer exercises and links to video lectures.

Research

Gerstner's research is focused on models of spiking neurons,[8][6] spike-timing-dependent plasticity (STDP),[9][10][11] neuronal coding in single neurons and neuron populations.[12][13][14][15][16] He also investigates models of the hippocampus and their application in the spatial representation for navigation of rat-like autonomous agents.[17]

He is also one of the initiators of The Deep Artificial Composer (DAC), a deep-learning algorithm that can generate melodies by imitating a given style of music.[18][19][20][21]

Scientific Publications (most cited)

  • Gerstner, W., Kempter, R., Van Hemmen, J.L. and Wagner, H., 1996. A neuronal learning rule for sub-millisecond temporal coding. Nature, 383(6595), pp. 76–78[22]
  • Brette, R. and Gerstner, W., 2005. Adaptive exponential integrate-and-fire model as an effective description of neuronal activity. Journal of neurophysiology, 94(5), pp. 3637–3642.[8]
  • Millan, J.R., Renkens, F., Mourino, J. and Gerstner, W., 2004. Noninvasive brain-actuated control of a mobile robot by human EEG. IEEE Transactions on biomedical Engineering, 51(6), pp. 1026–1033.[23]
  • Kempter, R., Gerstner, W., and Van Hemmen, J.L., Hebbian learning and spiking neurons. Physical Review E 59 (4), 4498-4514[24]

Distinctions

Gerstner has been an editorial board member of journals such as Science,[25] The Journal of Neuroscience, Network: Computation in Neural Systems, Journal of Computational Neuroscience,[1] and Neural Computation.

He is the recipient of the Valentino Braitenberg Award for Computational Neuroscience 2018[26] and in 2010 he was awarded an ERC Advanced Grant by the European Research Council.[27] Gerstner is an elected member of the Academy of Sciences and Literature Mainz.[28]

References

  1. ^ a b c "Wulfram Gerstner". people.epfl.ch. Retrieved 2020-09-04.
  2. ^ GERSTNER, Wulfram (1991). [papers.nips.cc/paper/371-associative-memory-in-a-network-of-biological-neurons.pdf "Associative memory in a network of biological neurons"] (PDF). Advances in Neural Information Processing Systems. 3: 84–90. {{cite journal}}: Check |url= value (help)
  3. ^ Gerstner, Wulfram; Abbott, L.F. (1997-01-01). "Learning Navigational Maps Through Potentiation and Modulation of Hippocampal Place Cells". Journal of Computational Neuroscience. 4 (1): 79–94. doi:10.1023/A:1008820728122. ISSN 1573-6873.
  4. ^ GERSTNER, Wulfram (1995). "Time structure of the activity in neural network models". Physical Review E. 51: 738.
  5. ^ "Wulfram Gerstner CV". lcnwww.epfl.ch. Retrieved 2020-09-04.
  6. ^ a b Gerstner, Wulfram. (2002). Spiking neuron models : single neurons, populations, plasticity. Kistler, Werner M., 1969-. Cambridge, U.K.: Cambridge University Press. ISBN 0-511-07817-X. OCLC 57417395.
  7. ^ Gerstner, Wulfram. (24 July 2014). Neuronal dynamics : from single neurons to networks and models of cognition. Kistler, Werner M., 1969-, Naud, Richard., Paninski, Liam. Cambridge, United Kingdom. ISBN 978-1-107-06083-8. OCLC 861774542.{{cite book}}: CS1 maint: location missing publisher (link)
  8. ^ a b Brette, Romain; Gerstner, Wulfram (2005-11-01). "Adaptive Exponential Integrate-and-Fire Model as an Effective Description of Neuronal Activity" (PDF). Journal of Neurophysiology. 94 (5): 3637–3642. doi:10.1152/jn.00686.2005. ISSN 0022-3077. PMID 16014787.
  9. ^ Gerstner, Wulfram; Kempter, Richard; van Hemmen, J. Leo; Wagner, Hermann (1996-09-05). "A neuronal learning rule for sub-millisecond temporal coding". Nature. 383 (6595): 76–78. Bibcode:1996Natur.383...76G. doi:10.1038/383076a0. ISSN 1476-4687. PMID 8779718. S2CID 4319500.
  10. ^ Zenke, Friedemann; Agnes, Everton J.; Gerstner, Wulfram (2015-04-21). "Diverse synaptic plasticity mechanisms orchestrated to form and retrieve memories in spiking neural networks". Nature Communications. 6 (1): 6922. Bibcode:2015NatCo...6.6922Z. doi:10.1038/ncomms7922. ISSN 2041-1723. PMC 4411307. PMID 25897632.
  11. ^ Clopath, Claudia; Büsing, Lars; Vasilaki, Eleni; Gerstner, Wulfram (2010-01-24). "Connectivity reflects coding: a model of voltage-based STDP with homeostasis" (PDF). Nature Neuroscience. 13 (3): 344–352. doi:10.1038/nn.2479. ISSN 1097-6256. PMID 20098420. S2CID 8046538.
  12. ^ Gerstner, Wulfram (2000-01-01). "Population Dynamics of Spiking Neurons: Fast Transients, Asynchronous States, and Locking". Neural Computation. 12 (1): 43–89. doi:10.1162/089976600300015899. ISSN 0899-7667.
  13. ^ Pozzorini, Christian; Naud, Richard; Mensi, Skander; Gerstner, Wulfram (July 2013). "Temporal whitening by power-law adaptation in neocortical neurons". Nature Neuroscience. 16 (7): 942–948. doi:10.1038/nn.3431. ISSN 1546-1726.
  14. ^ Jimenez Rezende, Danilo; Gerstner, Wulfram (2014-04-04). "Stochastic variational learning in recurrent spiking networks". Frontiers in Computational Neuroscience. 8: 38. doi:10.3389/fncom.2014.00038. ISSN 1662-5188. PMC 3983494. PMID 24772078.{{cite journal}}: CS1 maint: unflagged free DOI (link)
  15. ^ Vogels, T. P.; Sprekeler, H.; Zenke, F.; Clopath, C.; Gerstner, W. (2011-11-10). "Inhibitory Plasticity Balances Excitation and Inhibition in Sensory Pathways and Memory Networks". Science. 334 (6062): 1569–1573. Bibcode:2011Sci...334.1569V. doi:10.1126/science.1211095. ISSN 0036-8075. PMID 22075724. S2CID 45134325.
  16. ^ Hennequin, Guillaume; Vogels, Tim P.; Gerstner, Wulfram (2014-06-18). "Optimal Control of Transient Dynamics in Balanced Networks Supports Generation of Complex Movements". Neuron. 82 (6): 1394–1406. doi:10.1016/j.neuron.2014.04.045. ISSN 0896-6273. PMC 6364799. PMID 24945778.
  17. ^ Sheynikhovich, Denis; Chavarriaga, Ricardo; Strösslin, Thomas; Arleo, Angelo; Gerstner, Wulfram (2009-07-01). "Is there a geometric module for spatial orientation? Insights from a rodent navigation model" (PDF). Psychological Review. 116 (3): 540–566. doi:10.1037/a0016170. ISSN 1939-1471. PMID 19618986.
  18. ^ "From Mozart to Botzart: when machines write our music". phys.org. Retrieved 2020-09-04.
  19. ^ "Ein Algorithmus macht Musik - Wer hat's komponiert? Maschine oder Mensch?". Schweizer Radio und Fernsehen (SRF) (in German). 2017-07-25. Retrieved 2020-09-04.
  20. ^ "Ein Algorithmus lernt zu komponieren". Neue Zürcher Zeitung. 2017-07-06. Retrieved 2020-09-04.{{cite web}}: CS1 maint: url-status (link)
  21. ^ "Quand les algorithmes donnent le tempo". Le Temps (in French). 2017-08-25. ISSN 1423-3967. Retrieved 2020-09-04.
  22. ^ Gerstner, Wulfram; Kempter, Richard; van Hemmen, J. Leo; Wagner, Hermann (September 1996). "A neuronal learning rule for sub-millisecond temporal coding". Nature. 383 (6595): 76–78. doi:10.1038/383076a0. ISSN 0028-0836.
  23. ^ del R. Millan, J.; Renkens, F.; Mourino, J.; Gerstner, W. (2004-05-24). "Noninvasive Brain-Actuated Control of a Mobile Robot by Human EEG" (PDF). IEEE Transactions on Biomedical Engineering. 51 (6): 1026–1033. doi:10.1109/TBME.2004.827086. ISSN 0018-9294. PMID 15188874. S2CID 12537424.
  24. ^ Kempter, Richard; Gerstner, Wulfram; van Hemmen, J. Leo (1999-04-01). "Hebbian learning and spiking neurons". Physical Review E. 59 (4): 4498–4514. doi:10.1103/PhysRevE.59.4498. ISSN 1063-651X.
  25. ^ "Science Magazine Masterhead" (PDF). 2008-12-12. Retrieved 2020-09-04.{{cite web}}: CS1 maint: url-status (link)
  26. ^ "Wulfram Gerstner receives Valentino Braitenberg Award 2018 — Bernstein Netzwerk Computational Neuroscience". www.bernstein-network.de. Retrieved 2020-09-04.
  27. ^ "ERC Advanced Grant 2010" (PDF). 2010-01-20. Retrieved 2020-09-10.{{cite web}}: CS1 maint: url-status (link)
  28. ^ "Prof. Dr. Wulfram Gerstner : Akademie der Wissenschaften und der Literatur | Mainz". www.adwmainz.de. Retrieved 2020-09-04.
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